Kriging is a tool which produces ‘N’ dimensional approximation for the training data. Given a file containing data with both independent and dependent variables, we intend to model the relation between these variables. By using this model, we can find the output for the new input data. The independent variables can be of any of dimension while the dependent variables is restricted to only one dimension.
The core dependencies are:
- numpy
- matplotlib
- scipy
- inspyred
- Tkinter
$ git clone https://github.com/sankasuraj/sdesproject2.git
$ cd sdesproject2
$ pip install -r requirements.txt
$ python setup.py install
Kriging has been developed as a part of AE 663 (Software Development Techniques in Engineering and Science) project at IIT Bombay
Lead Developers:
- Sanka Suraj
- Vinodkumar Metla
- Mrinalgouda Patil
See also the list of contributors who participated in this project.
The latest documentation for kriging is available at http://kriging.readthedocs.io/
We like to thank our Professors for giving opportunity to take part in this project.
- Prabhu Ramachandran
- Madhu Belur
- Kumar Appaiah